Network-based services commonly provide information to influence or attract a particular group of users based on the interest or locality of the group. For example, a network-based advertising campaign may involve disseminating advertising information that is tailored for a target group based on the interest, behavior, or locality of the users in the group. Accordingly, the advertising campaign may provide the target group with information that is invaluable to users within the target group, but is less meaningful to users outside of the target group. Thus, determining an appropriate target group for disseminating information to is often the first step in creating an effective advertising campaign. In order to determine the appropriate target group for an effective campaign, various user attributes from user profile information are often used. For example, if an advertising campaign is targeted for a group of young females who have purchased XYZ perfume, attributes such as age and purchase history may be obtained from the user profile information. However, user profile information is not always available for users, especially for those potential users who do not register with the service and/or have no intention to provide user profile information.
Many network-based services want to attract potential users by providing relevant advertising or other meaningful information targeting the potential users. This is particularly true when potential users visit and interact with the network-based service, e.g., via a website for the network-based service. While potential users are interacting with the website, the well-targeted information can lead those potential users to request network services that are conveniently accessible via the website. Generally, each interaction or “click” on the website can provide some information (hereinafter “clickstream data”) about a potential user, e.g., the Internet Protocol (IP) address information of the computing device being used by the user. Although there have been some attempts to utilize IP address information for predicting or guessing profile information of the potential user, the ability to accurately and efficiently target potential users by predicting or guessing user attributes based on clickstream data is not quite developed. Further, even if certain user attributes can be predicted based on the clickstream data, it is difficult to estimate the accuracy of the predicted user attributes.